PSVIII-29 Nutritional Epigenetic Modifications in Beef Cattle
Bibliographic record
Abstract
Abstract Nutrition of the beef cow during pregnancy influences fetal development and potential changes in phenotype. On average 9 to 10% of the beef cattle herd are below the optimal body condition score of 2.5/5 at both pre-breeding and pregnancy tests, indicating potential nutritional stress during gestation. Epigenetic modifications are reported to regulate the changes in phenotype due to maternal nutrition during gestation. Our objective was to evaluate the influence of maternal nutrition during gestation on possible epigenetic mechanisms regulating development and biological function in Longissimus dorsi (LD) and Semimembranosus (SM) muscles, and liver (LV) at slaughter in steer progeny born from dams fed two different planes of nutrition during gestation. We also wanted to explore if the genetic potential of the offspring for residual feed intake (RFI) would interact with prenatal maternal diet to have differential effects on these epigenetic mechanisms. Purebred Angus steer calves (n = 23) were born from dams which were fed a diet formulated for an average daily gain (ADG) of either 0.5 or 0.7 kg/d from 30 to 150 days of gestation. Mating was designed so that calves were born from parents with differential genetic potential for high or low RFI. Calves were raised together as per normal industry standards and fed to be slaughtered as finished steers at approximately 512.1 ± 10.1 days of age. One approximately 10 g sample each of LV, LD, and SM muscles was aseptically collected within 30 to 45 min post-mortem and snap frozen in liquid nitrogen and subsequently stored at -80°C. Both DNA and RNA were isolated from the tissue samples and investigated for differences in methylation and gene expression, respectively. Fifteen potentially differently methylated regions (DMRs) in the DNA were measured using EpiTYPER MassARRAY technology, while expression of genes corresponding to the potential DMRs was measured by the nCounter Element Tagset by NanoString technologies. Average methylation across each DMR as well as gene expression within each tissue was profiled using principal component analyses (PCA). Distinct clustering was seen within both DNA methylation and gene expression PCAs such that the two muscles were clustered together and were separate from DNA methylation and gene expression measured in LV, representing expected functional variation due to tissue type. Between LD and SM, methylation patterns in the two muscles overlap, while there is much less overlap in gene expression patterns. This implies that the methylation pattern between the two muscle types is relatively similar compared with their patterns in gene expression, and that smaller differences in DNA methylation may lead to relatively larger differences in gene expression. These analyses are an important first step to interrogate the quality of our data that will be further analyzed for responses to maternal diet treatment and selection for genetic potential for RFI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".